Today's generative models have had wide-ranging successes
of modeling non-trivial probability distributions that
naturally arise in fields such as
physics [1]}, [2]},
climate science [3]},
and reinforcement learning [4]}.
Generative modeling on “straight” spaces (i.e., Euclidean) are pretty
well-developed and include (continuous) normalizing flows
[5]}, [6]}, [7]},
generative adversarial networks
[8]},
and variational auto-encoders
[9]}, [10]}.
